WHILE national AI discourse remains fixated on driving adoption numbers, our data says Malaysians are becoming active AI users faster than they are becoming confident AI workers.

In a single year, Malaysia’s score in the 2026 WiN World AI Index rose from 60.5 to 67.4, placing us sixth globally in overall AI adoption, behind India, China, Paraguay, Morocco and Indonesia. This index measures grassroots engagement across daily usage, trust, efficiency, and usability — where higher scores in peer markets like Paraguay and Morocco reflect strong daily usage frequency and perceived efficiency gains as people experiment with new tools.

In fact, 50.1% of all adult Malaysians and 57.7% of full-time working adults use AI regularly or daily for professional purposes, compared with 31% globally. Yet despite rapid adoption towards an AI economy, Malaysians’ comfort with living and working alongside AI fell from 42.5 to 38.7.

This disconnect highlights a growing vulnerability in the workplace, directly feeding into Malaysia’s +9 net worried score on AI-driven job replacement. Disruption is already occurring at the task level, from drafting and customer service to document review and routine analysis. Job titles may remain intact, but the core responsibilities within them are being restructured.

We see this as a critical gap. Malaysians may be embracing AI quickly, but adoption alone tells us little about whether workers feel equipped for what comes next.

This is why broad calls to “upskill” are insufficient. Malaysians need clarity on which skills retain value, which adjacent roles are growing, which training employers recognise, and what a viable transition path looks like.

The good news is that Malaysia has started with the right foundations. AI is no longer being treated only as a technology deployment issue. Through AI Malaysia and the National AI Action Plan 2026-2030, there is now a national effort to coordinate sector adoption, data governance, and talent development. Malaysia has also begun mapping how jobs are changing through agencies such as Kesuma, TalentCorp, MyMAHIR and PACE programme, guiding workers towards new career pathways rather than speaking about future skills in abstract terms.

However, a critical gap in Malaysia’s current strategy is the absence of concrete, sector-specific benchmarks to track whether these reskilling initiatives translate into workplace productivity and job stability. This oversight puts working Malaysians at risk. While technological change can create economic gains, this means little to workers displaced without a clear path forward.

Rather than evaluating success by course completion or general digital literacy rates, agencies must establish standardised benchmarks tailored to key growth sectors like manufacturing, services, and technology. This alignment is essential to capturing regional net growth, and

World Bank data shows Asean robot adoption between 2018 and 2022 created two million new skilled jobs while displacing 1.4 million low-skilled roles.

That said, new opportunities do not automatically accrue to displaced workers. Young Malaysians entering the labour market may face automation before securing full-time work, while existing workers find their roles changing faster than training systems can respond.

As president of the Market Research Society of Malaysia, one of the questions I believe we need to ask more rigorously is not simply how many Malaysians are using AI, but whether we are measuring how prepared people are for the changes it is creating.

To bridge this gap, Malaysia should track workforce readiness alongside adoption. This means mapping how jobs are changing by sector, which roles workers can realistically move into, what skills and industry-recognised programmes are required, and where employer demand exists. AI readiness must become a national workforce and education priority, with schools, TVET institutions, universities, employers and policymakers aligned around areas where human value will grow, from judgement and creativity to problem-solving, engineering, research, design, communication and accountability.

Other countries are not simply encouraging people to use AI. They are trying to understand how AI changes work, and then adjusting their labour and education systems around how work is changing. Our data in Gallup International's global findings show that concern about AI displacement generally declines in higher-income and more highly educated societies, where workers feel better cushioned and equipped to adapt.

Australia (-21 net worried score, where a negative score indicates significantly lower concern about job loss) began with evidence — producing a whole-of-labour-market study on generative AI to evaluate AI exposure, labour-market dynamism and skills adaptation before designing workforce interventions.

China took a more aggressive route through rapid structural alignment. When policymakers recognised that existing programmes no longer matched the economy being built, they approved 1,839 new undergraduate programmes, suspended enrolment for 2,220, and cancelled 1,428 to realign higher education pathways with emerging technologies and strategic industries.

Meanwhile, in Japan, (-23 net worried score), OECD data shows workers do not view AI as a threat, but as a necessary tool to offset labour shortages, framing technology as a way to complement human performance.

For Malaysia, these international models show that adoption alone will not build public confidence without a clear strategy tied to real workforce needs. We have adoption momentum and enough data to act. What we need now is a clearer handoff from AI ambition to workforce transition.

See Toh Wai Yu is the CEO of Central Force Insights & president of the Malaysian Market Research Society.